Residential Self-Selection and Travel:

Most Western national governments aim to influence individual travel patterns – at least to some degree – through the spatial planning of residential areas. Nevertheless, the extent to which the characteristics of the built environment influence travel behaviour remains the subject of debate among travel behaviour researchers. This work addresses the role of residential-self-selection, an important issue within this debate. Households may not only adjust their travel behaviour to the built environment where they live, but they may also choose a residential location that corresponds to their travel-related attitudes. The empirical analysis in this work is based on data collected through an internet survey and a GPS-based survey, both of which were conducted among homeowners in three centrally located municipalities in the Netherlands. The study showed that residential self-selection has some limited effect on the relationship between distances to activity locations and travel mode use and daily kilometres travelled. The results also indicate that the inclusion of attitudes can help to detecting residential self-selection, provided that studies comply with several preconditions, such as the inclusion of the ‘reversed’ influence of behaviour on attitudes

A Method for Deriving Trip Destinations and Modes for GPS-based Travel Surveys

This chapter contributes to the improvement of GPS-based travel surveying by introducing a combined method of GPS, GIS and web-based user interaction, which has been applied in large- scale fieldwork in the netherlands. With over 1000 participants, as far as we know, this is the first time that a GPS-based method that measures travel mode choice as well as the location and type of destinations that are visited has been used on such a large scale. The chapter focuses in particular on the identification of travel modes and destinations, which is still an under-researched issue. Our approach concentrates on the issue of deriving and validating the purpose of trip destinations and travel modes, while also allowing reliable multi-day data collection. The method consists of an interpretation process and a validation process. The interpretation process uses spatial data (e.g. railways, shops) and characteristics of the respondents (e.g. home address, possession of cars) to interpret data from the logs. The travel behaviour data that result from this interpretation round can be adjusted and added to by the respondents in a validation application. The link between both processes is interactive; when new individual characteristics (e.g. the address of a friend’s house) are entered by the respondents, these characteristics will be used for further interpretation of the data. The remainder of this chapter is structured as follows. The following section gives an overview of the advantages and drawbacks of current GPS-based data collection methods that are suitable for measuring choice of travel mode and/or trip destinations. The subsequent section describes the GPS-based method that we developed and in section four the value of our method is evaluated by presenting the results of the fieldwork we recently undertook. The results are compared with results from an internet survey that was carried out at an earlier date and also with the Dutch Travel Survey (DTS) that uses paper diaries. The chapter ends with conclusions on the use of GPS-based methods for the collection of travel behaviour data and a discussion of future possibilities